Despite extensive knowledge of the molecular components involved in HlV-1 transcriptional regulation, there is a critical need to understand how these components interact kinetically to form a regulatory 'switch' that mediates establishment, maintenance, and reactivation of HIV-1 latency at the single-cell level. Our long-term goal is to develop interventions to inhibit or purge latent HIV reservoirs, or alternatively, direct all replicating HIV to enter a latent state. The objective of this particular project is to quantitatively analyze the gene-regulatory circuitry underlying HIV latency and to quantify the effects of drugs on HIV's gene-regulatory circuitry in different primary-cell latency models. Our rationale for this project is that quantitative single-cell imaging of HIV gene expression will enable us to elucidate the gene-regulatory circuitry that controls latency in primary cells just as we were able to eluciate key aspects of the HIV latency circuitry in Jurkat cells. We pioneered the use of single-cell imaging approaches to study the role of stochastic noise in HIV gene expression and our analysis has elucidated that HlV-1 utilizes transcriptional positive feedback via Tat to amplify stochastic fluctuations in HIV gene expression and thereby establish a probabilistic molecular 'switch' between proviral latency and active infection (Weinberger et al. Cell 2005). that host SirT1 dampens fluctuations in Tat feedback (Weinberger & Shenk, PLoS Biology 2007), and that manipulating the feedback strength, in the J-lat latency model, can bias infected cells towards maintaining latency and not reactivating (Weinberger et al. Nature Genetics, 2008). We will employ microfluidic approaches and quantitative time-lapse imaging of HIV gene-expression to quantitatively compare the single-cell level effects of diverse drug candidates upon induction of latent gene expression in different primary-cell models. The resulting analysis will allow different drug candidates to be quantitatively compared in terms of their effect on gene expression in single cells and will guide molecular analyses in other projects within the collaboratory.